Identity Fraud Detection Pipeline (Real-time)
Designed a real-time fraud detection pipeline ingesting identity events via Kafka, executing PySpark operations, and writing outputs to Delta Lake.
Confidence S. is a Data Engineer with several years of experience in designing and implementing data pipelines and warehouses across various cloud platforms. His core technologies include Python, SQL, and Spark, which he uses to build ELT and ETL pipelines, real-time data ingestion systems, and automated workflows. Confidence is proficient with tools such as Apache Kafka, DBT, and Airflow, and is experienced in managing data warehouses on platforms like BigQuery and AWS Redshift. He ensures robust CI/CD practices using…
Designed a real-time fraud detection pipeline ingesting identity events via Kafka, executing PySpark operations, and writing outputs to Delta Lake.
Delivered a scalable data ingestion platform capable of processing various file types stored in AWS S3 into BigQuery using Airflow and Docker.
Lead the migration to Google BigQuery, engineered partitioning and clustering of tables, and constructed Airflow DAGs for automated loads.

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Confidence S. is a Data Engineer with several years of experience in designing and implementing data pipelines and warehouses across various cloud platforms. His core technologies include Python, SQL, and Spark, which he uses to build ELT and ETL pipelines, real-time data ingestion systems, and automated workflows. Confidence is proficient with tools such as Apache Kafka, DBT, and Airflow, and is experienced in managing data warehouses on platforms like BigQuery and AWS Redshift. He ensures robust CI/CD practices using…
Designed a real-time fraud detection pipeline ingesting identity events via Kafka, executing PySpark operations, and writing outputs to Delta Lake.
Delivered a scalable data ingestion platform capable of processing various file types stored in AWS S3 into BigQuery using Airflow and Docker.
Lead the migration to Google BigQuery, engineered partitioning and clustering of tables, and constructed Airflow DAGs for automated loads.
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